Mining Topological Patterns in Spatio-Temporal Databases

Mining Topological Patterns in Spatio-Temporal Databases

Wynne Hsu (National University of Singapore, Singapore), Mong Li Lee (National University of Singapore, Singapore) and Junmei Wang (National University of Singapore, Singapore)
Copyright: © 2008 |Pages: 36
DOI: 10.4018/978-1-59904-387-6.ch007
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In this chapter, we study the problem of mining topological patterns by imposing temporal constraints into the process of mining collocation patterns. We first introduce a summary structure that summarizes the database with the instances’ count information of a feature in a region within a time window. Next, based on the summary structure, we design an algorithm, called TopologyMiner, to find the interesting topological patterns in a depth-first manner. The algorithm follows the pattern growth methodology. We also investigate an efficient way to incorporate geographical features in TopologyMiner.

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